Author(s)

Marilena Meira, Cristina M. Quintella, Erika M. de O. Ribeiro, Alexandre K. Guimarães, Mariana Andrade Santos, Gabriela Silva Cerqueira, Alexandre Lopes Del Cid, Saionara Luna, Weidson Leal Silva

Instituto de Educa??o, Ciência e Tecnologia da Bahia, Campus de Sim?es Filho, Sim?es Filho, Brasil.
Instituto de Química, Universidade Federal da Bahia, Campus de Ondina, Salvador, Brasil.

Total spectrofluorimetry associated with Principal Component Analysis (PCA) was used to discriminate samples of vegetable oil and animal fat. In addition, a multivariate calibration model was developed that combines spectroflurimetry with Partial Least Squares (PLS) for prediction of concentration of animal fat in mixture with vegetable oil. The multivariate calibration model had an R² value of 0.98098, which indicates the accuracy of the model. This method has potential application in the control of quality of raw material for production of biodiesel. The control of the concentration of animal fat is important because animal fat is more susceptible to oxidation than vegetable oil. Furthermore, high concentrations of animal fats may increase electricity costs for biodiesel production due to the high melting points of saturated fats that solidify at room temperature and cause the fouling and clogging of pipes.

Biodiesel; Vegetable Oil; Animal Fat; Spectrofluorimetry; PLS

M. Meira, C. Quintella, E. Ribeiro, A. Guimarães, M. Santos, G. Cerqueira, A. Cid, S. Luna and W. Silva, "Prediction of Concentration of Animal Fat in Mixture with Vegetable Oil by Multivariate Calibration Associated with Spectrofluorimetry," American Journal of Analytical Chemistry, Vol. 4 No. 2, 2013, pp. 99-103. doi: 10.4236/ajac.2013.42013.